The future of service demands these 3 new capabilities from leaders

The role of the service leader is changing fast—and AI is at the center of that transformation. 

According to a recent Zendesk study, 83% of service leaders say they’re under pressure to accelerate AI adoption to improve operations and reduce costs. But traditional leadership models don’t account for all the ways AI is quietly reshaping their roles and the workforce itself. 

As service teams become hybrid (think: human-AI collaboration), leaders need to evolve beyond traditional people management. The new leadership toolkit involves coaching people, yes, but also managing an AI-augmented workforce and ensuring every decision said technology makes is governed and explainable. 

Here’s a closer look at the top capabilities service leaders now need:

1. Equip human agents to thrive in a hybrid workplace

Right now, contact centers continue to rely on large frontline teams that are volume-driven and expected to resolve a broad range of inquiries. But in the next few years, workforce design will shift to smaller, more expert teams that require higher skill expectations.

The roles of human agents will evolve from largely task-oriented to those that require emotional intelligence, complex problem-solving, and domain depth. According to our research, 87% of leaders believe human agents will elevate their roles to AI supervisors, managing 10-20 AI-assisted conversations simultaneously. 

That makes coaching your human agents and helping them develop the right skills pivotal to their success. With complexity comes new challenges—and stress—which also need to be managed. They’ll need to learn not only how to work alongside AI and manage prompts, but also how to handle more nuanced customer interactions and exercise judgment when automation falls short.

Upskilling employees will help yield improved business results. Enabled by tools like AI copilot, resolutions will be faster and more competent: 88% of service leaders say AI copilots will cut handling time by more than half. Plus, with the help of AI-surfaced insights, human agents will be able identify opportunities for upgrades or cross-selling. In this hybrid model, service will be faster and more personalized—meeting the rising demands of customers everywhere. 

2. Orchestrate operational flow for AI and human agents

AI is only as powerful as what it can access. Without secure, connected systems and knowledge, AI will deliver inconsistent answers to customers and employees, resulting in unreliable service that will ultimately erode trust. 

Service leaders are now on the hook to standardize the systems AI can access and unify knowledge sources. By doing so, AI will be able to provide instant solutions, whether it’s refunds, updates, troubleshooting, or policy lookups. 

With the right workflows in place, AI will also know how and when to escalate to a human. For example, if an issue is emotionally sensitive or technically complex, AI will seamlessly route the customer to a human agent without repeating steps or restarting the conversation. That way, the customer feels guided, not just handed off. 

Our research reveals that this level of AI-human collaboration is the future of service. In fact, 86% of leaders expect AI-driven self-service to surpass human-assisted resolution rates. And many leaders already see the benefit: 82% say customer satisfaction will be higher with AI-only interactions.

3. Govern AI to ensure transparent, auditable experiences 

This new era of AI in service is all about gaining trust—from customers and employees alike. As AI takes on higher-risk responsibilities, like making decisions and interacting directly with customers and employees, it raises the stakes for accuracy, consistency, and control. 

Service leaders—especially those in IT—are now responsible for defining guardrails, monitoring, and providing oversight for AI behavior. They’re also tasked with ensuring AI outputs are consistent, auditable, and aligned with company policies. 

Explainability will be critical: 92% of IT leaders say customers are more likely to trust AI responses when they include an explanation. If a team cannot audit how an AI model reached a specific decision, that model should not be placed in a customer-facing workflow. For customers to have true confidence in AI, trust must be engineered into the system from the beginning.

As AI reshapes the workplace, service leaders must evolve with it, equipping their teams with new skills, redesigning operations for a new way of working, and governing AI to ensure every experience is fair and transparent. By getting these foundations right, leaders can unlock the full potential of an AI-augmented workplace: better orchestration that saves time, faster and higher-quality resolutions, and stronger customer and employee experiences.